Using models to shape measles control and elimination strategies in low- and middle-income countries: A review of recent applications

Modelling the spatial variability and uncertainty for under-vaccination and zero-dose children in fragile settings

Universal access to childhood vaccination is important to child health and sustainable development. Here we identify, at a fine spatial scale, under-immunized children and zero-dose children. Using Chad, as an example, the most recent nationally representative household survey that included recommended vaccine antigens was assembled. Age-disaggregated population (12-23 months) and vaccination coverage were modelled at a fine spatial resolution scale (1km × 1 km) using a Bayesian geostatistical framework adjusting for a set of parsimonious covariates. There was a variation at fine spatial scale in the population 12-23 months a national mean of 18.6% (CrI 15.8%-22.6%) with the highest proportion in the South-East district of Laremanaye 20.0% (14.8-25.0). Modelled coverage at birth was 49.0% (31.2%-75.3%) for BCG, 44.8% (27.1-74.3) for DTP1, 24.7% (12.5-46.3) for DTP3 and 47.0% (30.6-71.0) for measles (MCV1). Combining coverage estimates with the modelled population at a fine spatial scale yielded 312,723 (Lower estimate 156055-409266) zero-dose children based on DTP1. Improving routine immunization will require investment in the health system as part of enhancing primary health care. The uncertainties in our estimates highlight areas that require further investigation and higher quality data to gain a better understanding of vaccination coverage.

Fractional-Order Epidemic Model for Measles Infection

In this study, a nonlinear dynamic SEVIQR measles epidemic model is constructed and analyzed using the novel Caputo fractional-order derivative operator. The model's existence and uniqueness are established. In addition, the model equilibria are determined, and the novel Jacobian determinant method recently constructed in the literature of epidemiological modeling of infectious diseases is applied to determine the threshold quantity, ℛ 0. Furthermore, we construct appropriate Lyapunov functions to establish the global asymptotic stability of the disease-free and endemic equilibrium points. Finally, the numerical solution of the model is executed employing the efficient and widely known Adams-type predictor-corrector iterative scheme, and simulation is conducted to investigate the impact of memory index and diverse preventive measures on the occurrence of the disease. Numerical simulation of the model indicates that quarantine, vaccination, and treatment can reduce the numbers of infectious and exposed populations, thereby controlling the disease. Therefore, it is recommended that the government provide financial assistance for vaccine distribution.

High-Resolution Geospatial Mapping of Zero-Dose and Underimmunized Children Following Nigeria's 2021 Multiple Indicator Cluster Survey/National Immunization Coverage Survey

BACKGROUND

"Zero-dose" children are those who are without any routine vaccination or are lacking the first dose of the diphtheria, tetanus, and pertussis-containing vaccine. Based on global estimates from the World Health Organization/United Nations Children's Fund in 2022, Nigeria has the highest number of zero-dose children, with >2.3 million unvaccinated.

METHODS

We used data from the 2021 Nigeria Multiple Indicator Cluster Survey/National Immunization Coverage Survey to identify zero-dose and underimmunized children. Geospatial modeling techniques were employed to determine the prevalence of zero-dose children and predict risk areas with underimmunized children at a high resolution (1 × 1 km).

RESULTS

Zero-dose and underimmunized children are more prevalent in socially deprived groups. Univariate and multivariate bayesian analyses showed positive correlations between the prevalence of zero-dose and underimmunized children and factors such as stunting, contraceptive prevalence, and literacy. The prevalence of zero-dose and underimmunized children varies significantly by region and ethnicity, with higher rates observed in the country's northern parts. Significant heterogeneity in the distribution of undervaccinated children was observed.

CONCLUSIONS

Nigeria needs to enhance its immunization system and coverage. Geospatial modeling can help deliver vaccines effectively to underserved communities. By adopting this approach, countries can ensure equitable vaccine access and contribute to global vaccination objectives.

Optimal Timing Regularly Outperforms Higher Coverage in Preventative Measles Supplementary Immunization Campaigns

Measles threatens the lives and livelihoods of tens of millions of children and there are countries where routine immunization systems miss enough individuals to create the risk of large outbreaks. To help address this threat, measles supplementary immunization activities are time-limited, coordinated campaigns to immunize en masse a target population. Timing campaigns to be concurrent with building outbreak risk is an important consideration, but current programmatic standards focus on campaigns achieving a high coverage of at least 95%. We show that there is a dramatic trade-off between campaign timeliness and coverage. Optimal timing at coverages as low as 50% for areas with weak routine immunization systems is shown to outperform the current standard, which is delayed by as little as 6 months. Measured coverage alone is revealed as a potentially misleading performance metric.

Possible Paths to Measles Eradication: Conceptual Frameworks, Strategies, and Tactics

Measles elimination refers to the interruption of measles virus transmission in a defined geographic area (e.g., country or region) for 12 months or more, and measles eradication refers to the global interruption of measles virus transmission. Measles eradication was first discussed and debated in the late 1960's shortly after the licensure of measles vaccines. Most experts agree that measles meets criteria for disease eradication, but progress toward national and regional measles elimination has slowed. Several paths to measles eradication can be described, including an incremental path through country-wide and regional measles elimination and phased paths through endgame scenarios and strategies. Infectious disease dynamic modeling can help inform measles elimination and eradication strategies, and all paths would be greatly facilitated by innovative technologies such as microarray patches to improve vaccine access and demand, point-of-contact diagnostic tests to facilitate outbreak responses, and point-of-contact IgG tests to identify susceptible populations. A pragmatic approach to measles eradication would identify and realize the necessary preconditions and clearly articulate various endgame scenarios and strategies to achieve measles eradication with an intensified and coordinated global effort in a specified timeframe, i.e., to "go big and go fast". To encourage and promote deliberation among a broad array of stakeholders, we provide a brief historical background and key considerations for setting a measles eradication goal.

Analysis of the yearly transition function in measles disease modeling

Globally, there were an estimated 9.8 million measles cases and 207 500 measles deaths in 2019. As the effort to eliminate measles around the world continues, modeling remains a valuable tool for public health decision-makers and program implementers. This study presents a novel approach to the use of a yearly transition function that formulates mathematically the vaccine schedules for different age groups while accounting for the effects of the age of vaccination, the timing of vaccination, and disease seasonality on the yearly number of measles cases in a country. The methodology presented adds to an existing modeling framework and expands its analysis, making its utilization more adjustable for the user and contributing to its conceptual clarity. This article also adjusts for the temporal interaction between vaccination and exposure to disease, applying adjustments to estimated yearly counts of cases and the number of vaccines administered that increase population immunity. These new model features provide the ability to forecast and compare the effects of different vaccination timing scenarios and seasonality of transmission on the expected disease incidence. Although the work presented is applied to the example of measles, it has potential relevance to modeling other vaccine-preventable diseases.

Evaluating effective measles vaccine coverage in the Malaysian population accounting for between-dose correlation and vaccine efficacy

BACKGROUND

Malaysia introduced the two dose measles-mumps-rubella (MMR) vaccine in 2004 as part of its measles elimination strategy. However, despite high historical coverage of MCV1 and MCV2, Malaysia continues to report high measles incidence. This study suggests a novel indicator for investigating population immunity against measles in the Malaysian population.

METHODS

We define effective vaccine coverage (EVC) of measles as the proportion of a population vaccinated with measles-containing vaccine (MCV) and effectively protected against measles infection. A quantitative evaluation of EVC throughout the life course of Malaysian birth cohorts was conducted accounting for both vaccine efficacy (VE) and between-dose correlation (BdC). Measles vaccination coverage was sourced from WHO-UNICEF estimates of Malaysia's routine immunisation coverage and supplementary immunisation activities (SIAs). United Nations World population estimates and projections (UNWPP) provided birth cohort sizes stratified by age and year. A step wise joint Bernoulli distribution was used to proportionate the Malaysian population born between 1982, the first year of Malaysia's measles vaccination programme, and 2021, into individuals who received zero dose, one dose and multiple doses of MCV. VE estimates by age and doses received are then adopted to derive EVC. A sensitivity analysis was conducted using 1000 random combinations of BdC and VE parameters.

RESULTS

This study suggests that no birth cohort in the Malaysian population has achieved > 95% population immunity (EVC) conferred through measles vaccination since the measles immunisation programme began in Malaysia.

CONCLUSION

The persistence of measles in Malaysia is due to pockets of insufficient vaccination coverage against measles in the population. Monitoring BdC through immunisation surveillance systems may allow for the identification of susceptible subpopulations (primarily zero-dose MCV individuals) and increase the coverage of individuals who are vaccinated with multiple doses of MCV. This study provides a tool for assessment of national-level population immunity of measles conferred through vaccination and does not consider subnational heterogeneity or vaccine waning. This tool can be readily applied to other regions and vaccine-preventable diseases.

Analysis of the different interventions scenario for programmatic measles control in Bangladesh: A modelling study

In recent years measles has been one of the most critical public health problem in Bangladesh. Although the Ministry of Health in Bangladesh employs a broad extension of measles control policies, logistical challenges exist, and there is significant doubt regarding the disease burden. Mathematical modelling of measles is considered one of the most effective ways to understand infection transmission and estimate parameters in different countries, such as Bangladesh. In this study, a mathematical modelling framework is presented to explore the dynamics of measles in Bangladesh. We calibrated the model using cumulative measles incidence data from 2000 to 2019. Also, we performed a sensitivity analysis of the model parameters and found that the contact rate had the most significant influence on the basic reproduction number R0. Four hypothetical intervention scenarios were developed and simulated for the period from 2020 to 2035. The results show that the scenario which combines enhanced treatment for exposed and infected population, first and second doses of vaccine is the most effective at rapidly reducing the total number of measles incidence and mortality in Bangladesh. Our findings also suggest that strategies that focus on a single interventions do not dramatically affect the decline in measles incidence cases; instead, those that combine two or more interventions simultaneously are the most effective in decreasing the burden of measles incidence and mortality. In addition, we also evaluated the cost-effectiveness of varying combinations of three basic control strategies including distancing, vaccination and treatment, all within the optimal control framework. Our finding suggested that combines distancing, vaccination and treatment control strategy is the most cost-effective for reducing the burden of measles in Bangladesh. Other strategies can be comprised to measles depending on the availability of funds and policymakers' choices.

Challenges Addressing Inequalities in Measles Vaccine Coverage in Zambia through a Measles-Rubella Supplementary Immunization Activity during the COVID-19 Pandemic

BACKGROUND

Measles-rubella supplementary immunization activities (MR-SIAs) are conducted to address inequalities in coverage and fill population immunity gaps when routine immunization services fail to reach all children with two doses of a measles-containing vaccine (MCV). We used data from a post-campaign coverage survey in Zambia to measure the proportion of measles zero-dose and under-immunized children who were reached by the 2020 MR-SIA and identified reasons associated with persistent inequalities following the MR-SIA.

METHODS

Children between 9 and 59 months were enrolled in a nationally representative, cross-sectional, multistage stratified cluster survey in October 2021 to estimate vaccination coverage during the November 2020 MR-SIA. Vaccination status was determined by immunization card or through caregivers' recall. MR-SIA coverage and the proportion of measles zero-dose and under-immunized children reached by MR-SIA were estimated. Log-binomial models were used to assess risk factors for missing the MR-SIA dose.

RESULTS

Overall, 4640 children were enrolled in the nationwide coverage survey. Only 68.6% (95% CI: 66.7%, 70.6%) received MCV during the MR-SIA. The MR-SIA provided MCV1 to 4.2% (95% CI: 0.9%, 4.6%) and MCV2 to 6.3% (95% CI: 5.6%, 7.1%) of enrolled children, but 58.1% (95% CI: 59.8%, 62.8%) of children receiving the MR-SIA dose had received at least two prior MCV doses. Furthermore, 27.8% of measles zero-dose children were vaccinated through the MR-SIA. The MR-SIA reduced the proportion of measles zero-dose children from 15.1% (95% CI: 13.6%, 16.7%) to 10.9% (95% CI: 9.7%, 12.3%). Zero-dose and under-immunized children were more likely to miss MR-SIA doses (prevalence ratio (PR): 2.81; 95% CI: 1.80, 4.41 and 2.22; 95% CI: 1.21 and 4.07) compared to fully vaccinated children.

CONCLUSIONS

The MR-SIA reached more under-immunized children with MCV2 than measles zero-dose children with MCV1. However, improvement is needed to reach the remaining measles zero-dose children after SIA. One possible solution to address the inequalities in vaccination is to transition from nationwide non-selective SIAs to more targeted and selective strategies.

Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria

Geographically precise identification and targeting of populations at risk of vaccine-preventable diseases has gained renewed attention within the global health community over the last few years. District level estimates of vaccination coverage and corresponding zero-dose prevalence constitute a potentially useful evidence base to evaluate the performance of vaccination strategies. These estimates are also valuable for identifying missed communities, hence enabling targeted interventions and better resource allocation. Here, we fit Bayesian geostatistical models to map the routine coverage of the first doses of diphtheria-tetanus-pertussis vaccine (DTP1) and measles-containing vaccine (MCV1) and corresponding zero-dose estimates in Nigeria at 1x1 km resolution and the district level using geospatial data sets. We also map MCV1 coverage before and after the 2019 measles vaccination campaign in the northern states to further explore variations in routine vaccine coverage and to evaluate the effectiveness of both routine immunization (RI) and campaigns in reaching zero-dose children. Additionally, we map the spatial distributions of reported measles cases during 2018 to 2020 and explore their relationships with MCV zero-dose prevalence to highlight the public health implications of varying performance of vaccination strategies across the country. Our analysis revealed strong similarities between the spatial distributions of DTP and MCV zero dose prevalence, with districts with the highest prevalence concentrated mostly in the northwest and the northeast, but also in other areas such as Lagos state and the Federal Capital Territory. Although the 2019 campaign reduced MCV zero-dose prevalence substantially in the north, pockets of vulnerabilities remained in areas that had among the highest prevalence prior to the campaign. Importantly, we found strong correlations between measles case counts and MCV RI zero-dose estimates, which provides a strong indication that measles incidence in the country is mostly affected by RI coverage. Our analyses reveal an urgent and highly significant need to strengthen the country's RI program as a longer-term measure for disease control, whilst ensuring effective campaigns in the short term.

Measles seroprevalence in persons over one year of age in Chandigarh, India

Measles continues to result in focal outbreaks in India, despite over three decades of universal infant vaccination. The aims of this study were to examine measles immunity in the population of Chandigarh, India, and to compare immunity by vaccination vs. natural infection. In a cross-sectional study of individuals 1-60 years selected from 30 communities within Chandigarh during 2017-2018, measles immunity was assessed using serological surveys. Seropositivity was compared across demographic groups, and by prior history of vaccination and natural history of infection. Among those 1-20 years old, measles seropositivity, and histories of measles vaccination or prior measles diagnosis were separately assessed as outcomes in logistic regression models, with demographic factors as independent variables. Among 1690 participants, 94% were seropositive, and 6% had borderline or negative antibody levels. Of those positive, 30% had prior vaccination, 16% had a history of natural infection, and 54% had an unknown history. Over 50% of individuals among those >20 years old, had unknown history of immunity. In the multivariable regression models, vaccination was more common in younger ages (P < .0001), and in males compared to females (P = .0220), and in those with more education (P < .0001). The majority of the population was seropositive, and seropositivity increased with age. Older age groups were more likely to be protected because of previous natural infection, whereas younger age groups were protected by vaccination. There was inequity in vaccination coverage by gender, and maternal education status.

Measles

Measles is a highly contagious, potentially fatal, but vaccine-preventable disease caused by measles virus. Symptoms include fever, maculopapular rash, and at least one of cough, coryza, or conjunctivitis, although vaccinated individuals can have milder or even no symptoms. Laboratory diagnosis relies largely on the detection of specific IgM antibodies in serum, dried blood spots, or oral fluid, or the detection of viral RNA in throat or nasopharyngeal swabs, urine, or oral fluid. Complications can affect many organs and often include otitis media, laryngotracheobronchitis, pneumonia, stomatitis, and diarrhoea. Neurological complications are uncommon but serious, and can occur during or soon after the acute disease (eg, acute disseminated encephalomyelitis) or months or even years later (eg, measles inclusion body encephalitis and subacute sclerosing panencephalitis). Patient management mainly involves supportive therapy, such as vitamin A supplementation, monitoring for and treatment of secondary bacterial infections with antibiotics, and rehydration in the case of severe diarrhoea. There is no specific antiviral therapy for the treatment of measles, and disease control largely depends on prevention. However, despite the availability of a safe and effective vaccine, measles is still endemic in many countries and causes considerable morbidity and mortality, especially among children in resource-poor settings. The low case numbers reported in 2020, after a worldwide resurgence of measles between 2017 and 2019, have to be interpreted cautiously, owing to the effect of the COVID-19 pandemic on disease surveillance. Disrupted vaccination activities during the pandemic increase the potential for another resurgence of measles in the near future, and effective, timely catch-up vaccination campaigns, strong commitment and leadership, and sufficient resources will be required to mitigate this threat.

Agent-Based Computational Epidemiological Modeling

The study of epidemics is useful for not only understanding outbreaks and trying to limit their adverse effects, but also because epidemics are related to social phenomena such as government instability, crime, poverty, and inequality. One approach for studying epidemics is to simulate their spread through populations. In this work, we describe an integrated multi-dimensional approach to epidemic simulation, which encompasses: (1) a theoretical framework for simulation and analysis; (2) synthetic population (digital twin) generation; (3) (social contact) network construction methods from synthetic populations, (4) stylized network construction methods; and (5) simulation of the evolution of a virus or disease through a social network. We describe these aspects and end with a short discussion on simulation results that inform public policy.

Mathematical modeling applied to epidemics: an overview

This work presents an overview of the evolution of mathematical modeling applied to the context of epidemics and the advances in modeling in epidemiological studies. In fact, mathematical treatments have contributed substantially in the epidemiology area since the formulation of the famous SIR (susceptible-infected-recovered) model, in the beginning of the 20th century. We presented the SIR deterministic model and we also showed a more realistic application of this model applying a stochastic approach in complex networks. Nowadays, computational tools, such as big data and complex networks, in addition to mathematical modeling and statistical analysis, have been shown to be essential to understand the developing of the disease and the scale of the emerging outbreak. These issues are fundamental concerns to guide public health policies. Lately, the current pandemic caused by the new coronavirus further enlightened the importance of mathematical modeling associated with computational and statistical tools. For this reason, we intend to bring basic knowledge of mathematical modeling applied to epidemiology to a broad audience. We show the progress of this field of knowledge over the years, as well as the technical part involving several numerical tools.

Every Child on the Map: A Theory of Change Framework for Improving Childhood Immunization Coverage and Equity Using Geospatial Data and Technologies

The effective use of geospatial data and technologies to collect, manage, analyze, model, and visualize geographic data has great potential to improve data-driven decision-making for immunization programs. This article presents a theory of change for the use of geospatial technologies for immunization programming-a framework to illustrate the ways in which geospatial data and technologies can contribute to improved immunization outcomes and have a positive impact on childhood immunization coverage rates in low- and middle-income countries. The theory of change is the result of a review of the state of the evidence and literature; consultation with implementers, donors, and immunization and geospatial technology experts; and a review of country-level implementation experiences. The framework illustrates how the effective use of geospatial data and technologies can help immunization programs realize improvements in the number of children immunized by producing reliable estimates of target populations, identifying chronically missed settlements and locations with the highest number of zero-dose and under-immunized children, and guiding immunization managers with solutions to optimize resource distribution and location of health services. Through these direct effects on service delivery, geospatial data and technologies can contribute to the strengthening of the overall health system with equity in immunization coverage. Recent implementation of integrated geospatial data and technologies for the immunization program in Myanmar demonstrate the process that countries may experience on the path to achieving lasting systematic improvements. The theory of change presented here may serve as a guide for country program managers, implementers, donors, and other stakeholders to better understand how geospatial tools can support immunization programs and facilitate integrated service planning and equitable delivery through the unifying role of geography and geospatial data.

Measles epidemiology and vaccination coverage in Oromia Region, Ethiopia: Evidence from surveillance, 2011-2018

Despite a reported high coverage of measles-containing vaccine (MCV), low-income countries including, Ethiopia, have sustained high measles transmission with frequent outbreaks. We investigated the distribution of measles infection and vaccination in Oromia Regional State, Ethiopia. According to the World Health Organization (WHO) and the Ethiopian measles case classification guidelines, measles cases were classified as laboratory-confirmed, clinically compatible, and epidemiologically linked. We derived measles vaccination coverage estimates using reported measles vaccine efficacy and, the proportion of measles cases vaccinated with measles vaccine at least once from the surveillance data. We calculated measles effective reproduction number (R_e) in the region. Almost twenty-five thousand measles cases were reported through the surveillance system, with more than 50% of the suspected and confirmed measles cases reported in 2015. Measles had sustained and high transmission rate with uneven distribution among the zones. Children between 1 and 4 years of age and MCV unvaccinated individuals were the most affected groups. In all the zones, the average surveillance-estimated MCV coverage among both infants and under-five children was significantly lower than the WHO recommended minimum 90% threshold herd-immunity. With this level of vaccination coverage, an infected case can transmit to more than four individuals. Nevertheless, the administrative coverage reports for the concurrent period were consistently above 90%. The estimated MCV coverage across the Oromia region was well below the recommended herd-immunity threshold. It partly explains the apparent mismatch of sustained measles transmission and outbreaks despite the very high administrative coverage estimates. Oromia regional health bureau, in collaboration with key stakeholders, should make a concerted effort to increase the effective-coverage of MCV to at least 90%. Additionally, multiple-dose MCV has to be scaled-up and accompanied with appropriate geographic and age targeting using evidence from surveillance data. Immediate programmatic action is needed to improve the quality of measles surveillance.

Measles, mumps, rubella prevention: how can we do better?

INTRODUCTION

Measles, mumps, and rubella incidence decreased drastically following vaccination programs' implementation. However, measles and mumps' resurgence was recently reported, outbreaks still occur, and challenges remain to control these diseases.

AREAS COVERED

This qualitative narrative review provides an objective appraisal of the literature regarding current challenges in controlling measles, mumps, rubella infections, and interventions to address them.

EXPERT OPINION

While vaccines against measles, mumps, and rubella (including trivalent vaccines) are widely used and effective, challenges to control these diseases are mainly related to insufficient immunization coverage and changing vaccination needs owing to new global environment (e.g. traveling, migration, population density). By understanding disease transmission peculiarities by setting, initiatives are needed to optimize vaccination policies and increase vaccination coverage, which was further negatively impacted by COVID-19 pandemic. Also, awareness of the potential severity of infections and the role of vaccines should increase. Reminder systems, vaccination of disadvantaged, high-risk and difficult-to-reach populations, accessibility of vaccination, healthcare infrastructure, and vaccination services management should improve. Outbreak preparedness should be strengthened, including implementation of high-quality surveillance systems to monitor epidemiology. While the main focus should be on these public health initiatives to increase vaccination coverage, slightly more benefits could come from evolution of current vaccines.

Challenges in measuring supplemental immunization activity coverage among measles zero-dose children

•Measles Supplemental Immunization Activities (SIAs) are resource intensive. •SIAs importantly reach some previously unvaccinated (so-called measles zero-dose) children. •We highlight difficulties in measuring how many measles zero-dose children the SIA reaches. •We also suggest some other methods to improve estimation of SIA impact.

Vaccination strategies for measles control and elimination: time to strengthen local initiatives

BACKGROUND

Through a combination of strong routine immunization (RI), strategic supplemental immunization activities (SIA) and robust surveillance, numerous countries have been able to approach or achieve measles elimination. The fragility of these achievements has been shown, however, by the resurgence of measles since 2016. We describe trends in routine measles vaccine coverage at national and district level, SIA performance and demographic changes in the three regions with the highest measles burden.

FINDINGS

WHO-UNICEF estimates of immunization coverage show that global coverage of the first dose of measles vaccine has stabilized at 85% from 2015 to 19. In 2000, 17 countries in the WHO African and Eastern Mediterranean regions had measles vaccine coverage below 50%, and although all increased coverage by 2019, at a median of 60%, it remained far below levels needed for elimination. Geospatial estimates show many low coverage districts across Africa and much of the Eastern Mediterranean and southeast Asian regions. A large proportion of children unvaccinated for MCV live in conflict-affected areas with remote rural areas and some urban areas also at risk. Countries with low RI coverage use SIAs frequently, yet the ideal timing and target age range for SIAs vary within countries, and the impact of SIAs has often been mitigated by delays or disruptions. SIAs have not been sufficient to achieve or sustain measles elimination in the countries with weakest routine systems. Demographic changes also affect measles transmission, and their variation between and within countries should be incorporated into strategic planning.

CONCLUSIONS

Rebuilding services after the COVID-19 pandemic provides a need and an opportunity to increase community engagement in planning and monitoring services. A broader suite of interventions is needed beyond SIAs. Improved methods for tracking coverage at the individual and community level are needed together with enhanced surveillance. Decision-making needs to be decentralized to develop locally-driven, sustainable strategies for measles control and elimination.

Development and dissemination of infectious disease dynamic transmission models during the COVID-19 pandemic: what can we learn from other pathogens and how can we move forward?

The current COVID-19 pandemic has resulted in the unprecedented development and integration of infectious disease dynamic transmission models into policy making and public health practice. Models offer a systematic way to investigate transmission dynamics and produce short-term and long-term predictions that explicitly integrate assumptions about biological, behavioural, and epidemiological processes that affect disease transmission, burden, and surveillance. Models have been valuable tools during the COVID-19 pandemic and other infectious disease outbreaks, able to generate possible trajectories of disease burden, evaluate the effectiveness of intervention strategies, and estimate key transmission variables. Particularly given the rapid pace of model development, evaluation, and integration with decision making in emergency situations, it is necessary to understand the benefits and pitfalls of transmission models. We review and highlight key aspects of the history of infectious disease dynamic models, the role of rigorous testing and evaluation, the integration with data, and the successful application of models to guide public health. Rather than being an expansive history of infectious disease models, this Review focuses on how the integration of modelling can continue to be advanced through policy and practice in appropriate and conscientious ways to support the current pandemic response.

Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda

INTRODUCTION

In low- and middle-income countries (LMICs), household survey data are a main source of information for planning, evaluation, and decision-making. Standard surveys are based on censuses, however, for many LMICs it has been more than 10 years since their last census and they face high urban growth rates. Over the last decade, survey designers have begun to use modelled gridded population estimates as sample frames. We summarize the state of the emerging field of gridded population survey sampling, focussing on LMICs.

METHODS

We performed a systematic scoping review in Scopus of specific gridded population datasets and "population" or "household" "survey" reports, and solicited additional published and unpublished sources from colleagues.

RESULTS

We identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, some survey teams interviewed all households in each cluster or segment, and others sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation.

CONCLUSIONS

For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings.